Metamodeling elastic wave propagation using a mixed factorized Fourier encoder–decoder for online laser-ultrasound testing in additive manufacturing

International audienceLaser-ultrasound (LU) testing has emerged as a promising technique for characterizing the polycrystalline microstructure of metal components produced by wire-laser additive manufacturing (WLAM), with potential for real-time online application. Numerical models simulating elastic waves propagation provide valuable insights into the relationship between microstructural properties and laser-induced displacements, but their computational cost renders them impractical for automated high-throughput characterization. To overcome this limitation, we build a metamodel that maps a wide variety of two-dimensional anisotropic polycrystalline microstructures — simplified but representative of features commonly observed in WLAM — to simulated surface displacements. Addressing this challenging high-dimensional regression problem, several neural network surrogates relying on a novel combination of layers are investigated. Their architectures include usual convolutional encoder–decoder elements and spectral layers inspired from the Fourier neural operator (FNO) framework. These layers are adapted and some variants are proposed to provide versatility in network design. All metamodels can run both a forward and backward pass at least 100 times faster than a single forward call of the original model. The best architecture implies a trade-off between computational cost and accuracy. Notably, the architecture involving the channel-wise factorized variant of the spectral layers, which is characterized by a relatively small number of parameters, achieved the lowest approximation error. The metamodel successfully captures the primary effects of anisotropy on wave propagation, even for low-anisotropy inputs not included in the training data. These findings represent a promising initial step towards addressing inversion problems and facilitating the development of online LU testing protocols in additive manufacturing

Capteurs sans batterie ou le mythe de l’autonomie infinie: Comment la variabilité et le vieillissement des composants impacte l’exécution de programmes ?

International audienceLes capteurs sans batterie, alimentés en puisant l'énergie présente dans l'environnement, promettent un fonctionnement autonome sans intervention humaine pendant de longues périodes. Limiter les distances parcourues pour les opérations de maintenance est un moyen de limiter l'impact environnemental des réseaux de capteurs, particulièrement significatif lorsqu'ils sont déployés dans des environnements difficiles d'accès.Cette promesse d'autonomie accrue reste cependant à démontrer. L'une des questions ouverte est l'impact des variations des caractéristiques des composants du capteurs sur la qualité de service . Ces variations sont causées par les conditions opératoires (température, humidité) mais aussi par le vieillissement naturel des matériaux. Nous nous intéressons ici au cas des (super)condensateurs utilisés comme tampon d'énergie

Efficient interaction-based offline runtime verification of distributed systems with lifeline removal

International audienceRuntime Verification (RV) refers to a family of techniques in which system executions are observed and confronted to formal specifications, with the aim of identifying faults. In offline RV, observation and verification are done in two separate and successive steps. In this paper, we define an approach to offline RV of Distributed Systems (DS) against interactions. Interactions are formal models describing communications within a DS. A DS is composed of subsystems deployed on different machines and interacting via message passing to achieve common goals. Therefore, observing executions of a DS entails logging a collection of local execution traces, one for each subsystem, collected on its host machine. We call multi-trace such observational artifacts. A major challenge in analyzing multi-traces is that there are no practical means to synchronize the ends of observations of all the local traces. We address this via an operation called lifeline removal, which we apply on-the-fly to the specification during the verification of a multi-trace once a local trace has been entirely analyzed. This operation removes from the interaction the specification of actions occurring on the subsystem that is no longer observed. This may allow further execution of the specification by removing potential deadlock. We prove the correctness of the resulting RV algorithm and introduce two optimization techniques, which we also prove correct. We implement a Partial Order Reduction (POR) technique by selecting a one-unambiguous action (as a unique first step to a linearization) whose existence is determined via the lifeline removal operator. Additionally, Local Analyses (LOC), i.e., the verification of local traces, can be leveraged during the global multi-trace analysis to prove failure more quickly. Experiments illustrate the application of our RV approach and the benefits of our optimizations

Scalable Structural Similarity Analysis of JSON documents Using MapReduce

International audienceThe increasing prevalence of JSON documents as a standard format for data storage and exchange in diverse applications has led to the need for efficient methods to compare and analyze hierarchical data structures. Traditional comparison methods often struggle with scalability and fail to account for structural variations in complex data formats. These limitations become particularly problematic in applications such as duplicate detection, anomaly analysis, and data integration, where accurate and scalable comparison of large JSON datasets is essential.To address these challenges, this paper presents a scalable framework for comparing JSON documents using the Aho-Hopcroft-Ullman (AHU) algorithm and the MapReduce paradigm. By generating canonical labels for hierarchical structures, the AHU algorithm captures structural similarities between JSON trees. The framework employs structural similarity measures, such as Longest Common Substring (LCS) and Levenshtein Distance, to quantify resemblance. MapReduce enables efficient processing of large JSON datasets, with a mapping phase for parsing and labeling and a reducing phase for similarity computations. This approach offers a robust and scalable solution for hierarchical data comparison, facilitating critical applications in duplicate detection and anomaly analysis.Index terms JSON comparison, AHU algorithm, structural similarity, MapReduce, hierarchical data, Levenshtein distance, LCS.</div

Critical safety risks for passengers onboard level 4 automated shuttles in Europe: mitigation strategies and public policy implications

A core value proposition of driverless automated vehicles (AVs) is reducing road accidents largely attributed to human errors and increasing traffic safety. Nonetheless, safety remains a foremost concern in the adoption of AVs. This paper enriches the academic and policy debate on driverless (level 4) AV safety for onboard passengers. We conduct semi-structured interviews with 47 Connected Cooperative Automated Mobility (CCAM) experts from diverse sectors and 11 European countries for insights into their views and opinions on the critical safety issues of driverless AV and possible mitigation strategies in Europe. Then, we conduct data analysis using reflexive thematic analysis. We find that the critical safety issues are injury, accident or death of passengers, adverse weather/environmental conditions, cybersecurity issues, perceived safety risks, and AV functional failure. We argue that the safety risks at specific locations in the extant literature are interlinked and are generalisable in the European context. The key mitigation strategies are monitoring in-vehicle conditions, designing AVs for functional safety, increasing road testing to improve AV perception and sensing technologies, user education and communication about AV, support from road infrastructure and V2X technologies. The other mitigation strategies are facilitating stakeholder collaboration, knowledge, and data sharing, enacting/enforcing safety standards and regulations, and separating AVs from human drivers. Then, we analyse the mitigation strategies using five governance policy steering instruments to understand workable public policy approaches to support policymaking on driverless (level 4) AV in Europe. We argue that a combination of governing by enabling and governing by authority policy steering instruments could support mitigating the critical safety risks of level 4 AVs. We argue that these policy steering instruments could support mitigating the critical safety risks of level 4 AVs and play a key role in supporting driverless AVs' safe integration into transportation systems and the transition to a connected, cooperative, automated mobility future in Europe.</div

Spectro-photometry of Phobos simulants, II: Effects of porosity and texture

International audienceSurface porosity and texture has been found to be an important property for small bodies. Some asteroids and comets can exhibit an extremely high surface porosity in the first millimeter layer. This layer may be produced by various processes and maintained by the lack of an atmosphere. However, the influence of porosity on the spectro-photometric properties of small body surfaces is not yet fully understood.In this study, we looked into the effect of the texture on the spectro-photometric properties of Phobos regolith spectroscopic simulants. Macro- and micro-porosity were created by mixing the simulants with ultra-pure water, producing ice-dust particles, and then sublimating the water. The sublimation of the water ice enabled the production of porous and rough powdered simulants with significant micro- and macro-porosity associated with macro-roughness. The reflectance spectroscopic properties in the visible and near-infrared (0.5–4.2m) demonstrate a brightening of the porous samples in comparison to the compact ones. One simulant exhibits a bluing of the spectral slope after increasing porosity, which is likely linked to the presence of expandable phyllosilicates. In the mid-infrared range, a contrast increase of the 10 m emissivity-related plateau due to silicates is observed. This spectral feature is typically observed as a 10m emissivity plateau on some asteroids, making the mid-infrared region important for assessing mineralogy and surface texture.Photometry reveals a modification of the phase reddening behavior between the compact powder and the sublimation residue for both simulants. However, the observed behavior is different between the simulants, suggesting that the phase reddening may be dependent on the composition of the simulants. The phase curves of the sublimation residues exhibit a higher contribution of forward scattering. The derivation of the Hapke parameters indicates an increase in roughness for the porous sample, but no significant modification of the opposition effect. The modifications of the spectrophotometric properties observed in this experiment are definitely due to the textural changes obtained after sublimation, which depend on the initial composition of the simulants.This study aims to provide new insights into the understanding of porosity by using two Phobos simulants in the context of the upcoming JAXA/Martian Moons eXploration mission. We suggest that the Phobos blue unit may be due to the presence of a highly porous layer, rather than only to space-weathering processes, as often postulated

Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption

Causal machine learning has the potential to revolutionize decision-making by combining the predictive power of machine learning algorithms with the theory of causal inference. However, these methods remain underutilized by the broader machine learning community, in part because current empirical evaluations do not permit assessment of their reliability and robustness, undermining their practical utility. Specifically, one of the principal criticisms made by the community is the extensive use of synthetic experiments. We argue, on the contrary, that synthetic experiments are essential and necessary to precisely assess and understand the capabilities of causal machine learning methods. To substantiate our position, we critically review the current evaluation practices, spotlight their shortcomings, and propose a set of principles for conducting rigorous empirical analyses with synthetic data. Adopting the proposed principles will enable comprehensive evaluations that build trust in causal machine learning methods, driving their broader adoption and impactful real-world use

Regulating TSO interaction in bid filtering for European balancing markets

International audienceEurope is undertaking projects for near real-time common balancing markets to meet the flexibility needs induced by renewable deployment. A new congestion management method, bid filtering, has been authorized by regulation to prevent unsolvable last minute congestion. It is designed to manage internal congestion and is performed by each Transmission System Operator (TSO) separately without knowledge of bids in other zones. Bids from all zones are shared in the same market, which means filtering from one TSO could affect welfare in other zones, depending on its objective and on regulation. This paper evaluates the potential effects of multiple TSOs interacting with different filtering strategies. Three TSO strategies are considered – Benevolent, Local, and Conservative – and different combinations are tested using multi-agent reinforcement learning. Results show that although several TSOs filtering benevolently leads to the highest net Social Welfare, it is unlikely that all TSOs will adopt this strategy considering political and social constraints in EU27 countries. We discuss several regulatory options to create the conditions for a Social Welfare-maximizing filtering and foster coordination between TSOs

A Comparative Study on Ray-Tracing and Physical-Optics Methods for the Analysis of Transmitarray Antennas

International audienceThis study compares the accuracy of two semi-analytical methods based on ray tracing (RT) and physical optics (PO) for the analysis and design of transmitarrays of different sizes. The assessment considers multiple focal-to-diameter ratios and eight unit cells implementing 3-bit uniform phase quantization at 30 GHz. The results, validated by full-wave simulations, demonstrate that both the RT and PO methods yield excellent agreement in standard-profile configurations. However, the RT approach, which assumes the transmitarray to be in the far-field region of the primary feed, provides a wrong evaluation of the gain of low-profile antennas, with errors up to 1.5 dB at 34 GHz. In contrast, the PO method accounts for near-field effects and accurately predicts the transmitarray performance even when the focal distance is comparable to the wavelength. Additionally, the PO method enables the analysis of large antennas with computational efficiency comparable to RT, requiring approximately four minutes for transmitarrays with diameters of 30 wavelengths

On the Design, Fabrication and Characterization of a Miniaturized and Optically Transparent CSRRs-Loaded Antenna Operating in C-Band for a Dual Optical-RF Purpose

International audienceA miniaturized and optically transparent CSRRs-loaded (Circular Split Ring Resonator) antenna operating in C-band is presented. Two miniaturization techniques were used to get a highly miniaturized microstrip antenna. By combining high-permittivity substrate with CSRRs-loaded ground plane, a reduction size over 70% was then obtained. The antenna dimension equals 0.1λ at fr=5.3 GHz with a −3.9dBi simulated gain. Optical transparency is achieved by printing a micrometric mesh metal films with pitch of 300 μm and metal strip width of 10 μm on both sides of sapphire substrate. Homemade prototypes were fabricated and characterized at microwaves: the operating frequency and radiation pattern were measured experimentally. Snapshots from an endoscopic camera were taken behind the transparent antenna as proof of concept. A new dual optical-RF application has therefore been developed